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Montblanc Radius Plate System

The Montblanc Radius Plate System is intended for internal fixation for fractures and reconstruction of the small bones, primarily including the distal radius and distal ulna. Examples of these internal fixations and reconstructions include compression fractures, intra-articular and extra-articular fractures, displaced fractures, osteotomies, non-unions and malunions. This system can be used for palmar, dorsal or orthogonal application.

Montblanc Ankle Plate System

The Montblanc Ankle Plate System is intended to be used for internal bone fixation for bone fractures, fusions, osteotomies and non-unions in the distal tibia and fibula.

The Montblanc Plate System consists of a series of plates and screws of varying lengths and orientations with Montblanc Radius Plate System and Montblanc Ankle Plate System. Each plate provides locking screw fixation. The proposed plates are manufactured from CP Grade 4 Titanium conforming to ASTM F67. The plates are sold as non-sterile, single-use.

The FDA 510(k) clearance letter for the Montblanc Plate System does not contain information about a study proving the device meets acceptance criteria related to AI/software performance. The provided document is for a mechanical bone fixation device (plates and screws), not an AI-powered diagnostic or assistive technology.

Therefore, many of the requested fields are not applicable to this type of medical device and its clearance process. The performance tests mentioned in the document are mechanical and material property tests for the physical plate and screw components, not software-based algorithms.

Here's an analysis based on the provided document, highlighting what is (and isn't) present:

Device Type: Montblanc Plate System (Single/multiple component metallic bone fixation appliances and accessories - plates and screws for fractures)

Nature of Device Performance Evaluation in 510(k): For this device, the "performance" evaluated by the FDA relates to the physical and mechanical properties of the plates and screws (e.g., strength, stiffness, resistance to forces) to ensure they can effectively fix bone fractures. It does not involve an AI algorithm or software for diagnosis or assistance, nor does it require human reader studies, ground truth establishment by experts, or training/test sets for AI.

Information from the Provided Document:

1. A table of acceptance criteria and the reported device performance:

The document mentions that performance tests were conducted in accordance with manufacturer SOP, FDA guidance, ASTM F382 (Standard Specification for Metallic Bone Plates), and ASTM F543 (Standard Specification for Metallic Medical Bone Screws). It specifies:

Note: The document states, "We believe that the performance test acceptance criteria is appropriate and that each test result ensure the effectiveness of Montblanc Plate System for the indications for use provided by the manufacturer and supports substantial equivalence." This statement implies that the device met the established acceptance criteria for these mechanical tests.

2. Sample sized used for the test set and the data provenance:

• Sample Size: The document mentions "Plates with the smallest cross-sectional area of the critical region of the device" and "Screws with the smallest cross-sectional area of the critical region of the device and longest length," and "Screws with the smallest cross-sectional area of the critical region of the device and shortest length" were chosen as worst-case samples. This suggests a limited, targeted number of physical samples for testing, focused on representative "worst-case" configurations to demonstrate mechanical robustness. It does not refer to a data set in the context of AI.
• Data Provenance (Country of Origin): Not specified for the tests, but the applicant (Medifield Medical Co., Ltd.) is from Korea, South.
• Retrospective or Prospective: Not applicable, as these are engineering/mechanical bench tests on physical devices.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not Applicable. This is a mechanical device, not an AI system requiring expert-established ground truth from medical images/data. The "ground truth" for mechanical properties is established by engineering standards (ASTM) and internal specifications.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

• Not Applicable. No human reader adjudication is involved in the mechanical testing of bone plates and screws.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

• Not Applicable. This device is a mechanical implant, not an AI-assisted diagnostic tool. No human reader studies or comparisons with AI assistance were performed.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

• Not Applicable. There is no algorithm or software component to evaluate in a standalone manner for this device.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

• Mechanical Engineering Standards and Specifications. For this type of device, the "ground truth" for performance is defined by adherence to established mechanical testing standards (e.g., ASTM F382, ASTM F543) and the manufacturer's own design specifications, which are based on biomechanical requirements for bone fixation.

8. The sample size for the training set:

• Not Applicable. This device does not use machine learning or AI, so there is no training set.

9. How the ground truth for the training set was established:

• Not Applicable. As there is no training set for AI, no ground truth needed to be established for it.

Summary of Key Takeaway:

The provided document describes the FDA 510(k) clearance for a mechanical medical device (bone plates and screws). The "acceptance criteria" and "study" proving the device meets these criteria refer to physical and mechanical bench testing against engineering standards, not to the performance of an artificial intelligence algorithm or software. Therefore, most of the questions related to AI performance metrics, data sets, expert review, and ground truth establishment from medical data are not relevant to this particular 510(k) submission.

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